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This is: Seemingly Popular Covid-19 Model is Obvious Nonsense, published by Zvi on the AI Alignment Forum.
Previous Covid-19 thoughts: On R0, Taking Initial Viral Load Seriously
Epistemic Status: Something Is Wrong On The Internet. Which should almost always be ignored even when you are an expert, and I am nothing of the kind. Thus, despite this seeming like a necessary exception, I expect to regret writing this.
People are taking the projection of 60,000 American deaths from Covid-19 as if it were a real prediction. This number is being used to make policy, to deny states medical equipment and to make plans that spend trillions of dollars and when to plan to reopen entire economies.
Ignoring this in the hopes it will go away does not seem reasonable.
My suspicions that this was necessary were more than confirmed when, failing to realize just how obvious the nonsense in question was and thinking I needed to justify labeling it nonsense, I wrote a reference post called The One Mistake Rule.
The second comment on that post was to argue that we should indeed use exactly the model that motivated me to write the post. The comment is here in full:
If a model gives a definitely wrong answer anywhere, it is useless everywhere.
Except if it needs to be used right now to make important decisions and it’s the best model we have. See:
We could plausibly think this is the best model we have? Oh my are we screwed.
The Baseline Scenario That Makes No Sense
There seems to be a developing consensus on many fronts, for now, that the model linked above represents our reality. The model says it is ‘designed to be a planning tool’ and that is exactly what is happening here.
What is this model doing? Time to look at the pdf.
Here’s the money quote that describes the core of what they are actually doing.
A covariate of days with expected exponential growth in the cumulative death rate was created using information on the number of days after the death rate exceeded 0.31 per million to the day when 4 different social distancing measures were mandated by local and national government:
School closures, non-essential business closures including bars and restaurants, stay-at-home recommendations, and travel restrictions including public transport closures. Days with 1 measure were counted as 0.67 equivalents, days with 2 measures as 0.334 equivalents and with 3 or 4 measures as 0. For states that have not yet implemented all of the closure measures, we assumed that the remaining measures will be put in place within 1 week. This lag between reaching a threshold death rate and implementing more aggressive social distancing was combined with the observed period of exponential growth in the cumulative death rate seen in Wuhan after Level 4 social distancing was implemented, adjusted for the median time from incidence to death. For ease of interpretation of statistical coefficients, this covariate was normalized so the value for Wuhan was 1.
In other words, this model assumes that social distancing measures work really, really well. Absurdly well. All you have to do to stop Covid-19 is any three of: Close schools, close non-essential businesses, tell people to stay at home, impose travel restrictions.
If you do that and maintain it, people stop dying. Entirely.
Look at the graph they have up as of this writing (updated on 4/10). By June 20, they predict actual zero deaths that day and every future day. They have us under 100 deaths per day by the end of May.
The peak in hospital use? Today, April 11.
The peak in deaths? Yesterday, April 10. For New York, several days ago, with our last death on May 20.
In other words, considering the delay in deaths is about three weeks, they predict that no one in New York State will be infected after April. No one! We’ll all be safe in only three weeks!
This is despite us ...
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